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RISS 인기검색어
- 검색키워드
- 저자 : Akbar Pattar (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
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Uyghur Stemming Using Conditional Random Fields
Abdurahim Mahmoud,Akbar Pattar,Askar Hamdulla 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.8
Stemming is a natural language processing task that to remove all derivational affixes from a word. This task proved to be harder for languages with complex morphology such as the Uyghur language. This paper presents a new stemming method for Uyghur words based on CRFs (Conditional Random Fields). In the proposed method all words in the training corpus are segmented into syllables and each syllable are tagged as a part of stem or as a part of affix. We experimentally evaluated this method with five test files each includes 100 sentences , results have shown that our method gets good performance, average stemming precision, recall and F-score in open test reached 98.42%, 98.34% and 98.38% respectively.
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The Intonation Pattern of Imperative Sentences in Uyghur Language
Seyyare Imam,Hankiz Yilahun,Akbar Pattar,Askar Hamdulla 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5
Based on the notion of intonation pattern and method of undulating scale computation, this paper has done a quantitative analysis to the intonation patterns of imperative oral sentences in standard Uyghur language. And give the pitch contour distributions of representative sentences and their different tone groups for the first time. The experimental results show that whether from the contour curves of overall sentences or fluctuations of tone groups pitch contour curves and the width variations, we can observe the distinctive features between different pronunciations. And can also observe the subtle tone differences between different types of statements voiced from a same text sentence.
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Stem-Affix based Uyghur Morphological Analyzer
Mijit Ablimit,Tatsuya Kawahara,Akbar Pattar,Askar Hamdulla 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.2
Uyghur language is an agglutinative language in which words are derived from stems (or roots) by concatenating suffixes. This property makes a large number of combinations of morphemes, and greatly increases the word-vocabulary size, causing out-of-vocabulary (OOV) and data sparseness problems for statistical models. So words are split into certain sub-word units and applied to text and speech processing applications. Proper sub-word units not only provide high coverage and smaller lexicon size, but also provide semantic and syntactic information which is necessary for downstream applications. This paper discusses a general purpose morphological analyzer tool which can split a text of words into sequence of morphemes or syllables. Uyghur morpheme segmentation is a basic part of the comprehensive effort of the Uyghur language corpus compilation. As there are no delimiters for sub-word units, a supervised method, combined with certain rules and a statistical learning algorithm, is applied for morpheme segmentation. For phonetic units like syllable and phonemes, pure rule-based methods can extract with high accuracy. Most common and proper sub-words for various applications can be the linguistic morphemes for they provide linguistic information, high coverage, low lexicon size, and easily be restored to words. As the Uyghur language is written as pronounced, phonetic alterations of speech are openly expressed in text. This property makes many surface forms for a particular morpheme. A general purpose morphological analyzer must be able to analyze and export in both standard and surface forms. So the morpho-phonetic alterations like phonetic harmony, weakening, and morphological changes are summarized and learnt from training corpus. And a statistical model based morpheme segmentation tool is trained on the corpus of aligned word-morpheme sequences, and applied to predict possible morpheme sequences. For an open test set, with word coverage of 86.8% and morpheme coverage of 98.4%, the morpheme segmentation accuracy is 97.6%. This morpheme segmentation tool can output both on the standard forms and on the surface forms without costing segmentation accuracy. Furthermore, for various basic lexical units of word, morpheme, and syllable, the statistical properties are compared as a comprehensive effort of the Uyghur language corpus compilation.
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The Vowel Harmony in Two-syllabic Uyghur Words and its Acoustical Analysis
Gulnur Arkin,Seyyare Imam,Akbar Pattar,Askar Hamdulla 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.4
A statistical analysis has been made on 969 two-syllabic words in Uyghur Acoustical Database. The major part of this paper concentrates on the basic acoustic features of two-syllabic harmonious words including formant frequency, resonance peak value, vowel duration, vowel pitch and the sound intensity. And we have summarized certain rules and conclusions of great importance for adjusting vowel harmony in parametric speech synthesis or waveform concatenated speech synthesis system.
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The Patterns of Vowels in Monosyllabic Words of Uyghur Language
Seyyare Imam,Aynur Nurtay,Akbar Pattar,Askar Hamdulla 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.3
In this paper, on the basis of traditional phonetics, by using the methods of experimental phonetics and voice pattern theory, Analyzed and summarized the vowel pattern of the monosyllables in Uyghur language. The statistical analysis is carried upon the vowel formant frequency values in monosyllables, and discussed by using Joos method in more details. For the first time, with the actual experimental data proves the accordance of tongue location features of Uyghur vowel with the traditional knowledge from hearsay. The research results of this paper will have a high reference value for the study and application development of both Uyghur language and the other languages are belongs Altaic language family.
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